FLTL: A Forward-Looking Approach

As noted in Section 1 above, the two key issues facing
approaches to NMRDPs are how to specify the reward functions compactly
and how to exploit this compact representation to automatically
translate an NMRDP into an equivalent MDP amenable to the chosen
solution method. Accordingly, our goals are to provide a reward
function specification language and a translation that are adapted to
anytime state-based solution methods. After a brief reminder of the
relevant features of these methods, we consider these two goals in
turn. We describe the syntax and semantics of the language, the notion
of formula progression for the language which will form the basis of
our translation, the translation itself, its properties, and its
embedding into the solution method. We call our approach FLTL. We
finish the section with a discussion of the features that distinguish
FLTL from existing approaches.
Subsections